Reductionism persists as a useful node in the possibility space of understanding and managing the world around us. However the possibility space is now expanding to higher levels of resolution such as a focus on complex systems. Learning and tools are ratcheting in lock-step.

Some of the key complexity-related concepts in understanding collective behavior in real-life physical systems like the burning of a forest fire include:

Organization and Self-Organization: Self-orchestration into order in both living and non-living systems, for example: salt crystals, graphene, protein molecules, schools of fish, flocks of birds, bee hives, intelligence and the brain, social structures

Order and Stability of Systems: Measurements of order, stability, and dynamical break-down in systems such as entropy, symmetry (and symmetry-breaking), critical point, phase transition, boundaries, and fractals (101 primer)

Tunable Parameters: An element or parameter which doesn’t control the system, but can be tuned to influence the performance of the system (for example, temperature is a tunable parameter in the complex system of water becoming ice)

Perturbation and Reset: How and how quickly systems reset after being perturbed is another interesting aspect of complex systems

Complexity science is not new as a field. What is new is first, a more congruous conceptual application of complexity thought in the sense of appreciating overall continuum of systems phenomena, not trying to grasp for the specific moment of a phase transition.

The other aspect that is new is the idea of working in an applied manner with complex systems, particularly with tools that are straightforward to implement like the math tools of non-linear dynamics, networks, chaos, fractals, and power laws (many inspired by the work of Stan Strogatz), and Software Tools like NetLogo, a multi-agent programmable modeling environment andChucK, a digital audio programming language.